Method and system for implementing dynamic treatment environments based on patient information

ABSTRACT

A system that comprises a memory device storing instructions, and a processing device communicatively coupled to the memory device. The processing device executes the instructions to: receive user data obtained from records associated with a user; generate a modified treatment plan based on the user data; and send, to a treatment apparatus accessible to the user, the modified treatment plan, wherein the modified treatment plan causes the treatment apparatus to update at least one operational aspect of the treatment apparatus, and update at least one operational aspect of at least one other device communicatively coupled to the treatment apparatus.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 17/021,895, filed Sep. 15, 2020, titled “Telemedicine forOrthopedic Treatment,” which claims priority to and the benefit of U.S.Provisional Patent Application Ser. No. 62/910,232, filed Oct. 3, 2019,titled “Telemedicine for Orthopedic Treatment,” the entire disclosuresof which are hereby incorporated by reference for all purposes.

BACKGROUND

Remote medical assistance, also referred to, inter alia, as remotemedicine, telemedicine, telemed, telmed, tel-med, or telehealth, is anat least two-way communication between a healthcare provider orproviders, such as a physician or a physical therapist, and a patientusing audio and/or audiovisual and/or other sensorial or perceptive(e.g., without limitation, gesture recognition, gesture control,touchless user interfaces (TUIs), kinetic user interfaces (KUIs),tangible user interfaces, wired gloves, depth-aware cameras, stereocameras, and gesture-based controllers, tactile, gustatory, haptic,pressure-sensing-based or electromagnetic (e.g., neurostimulation)communications (e.g., via a computer, a smartphone, or a tablet).Telemedicine may aid a patient in performing various aspects of arehabilitation regimen for a body part. The patient may use a patientinterface in communication with an assistant interface for receiving theremote medical assistance via audio, visual, audiovisual, or othercommunications described elsewhere herein. Any reference herein to anyparticular sensorial modality shall be understood to include and todisclose by implication a different one or more sensory modalities.

Telemedicine is an option for healthcare providers to communicate withpatients and provide patient care when the patients do not want to orcannot easily go to the healthcare providers' offices. Telemedicine,however, has substantive limitations as the healthcare providers cannotconduct physical examinations of the patients. Rather, the healthcareproviders must rely on verbal communication and/or limited remoteobservation of the patients.

SUMMARY

In one embodiment, a system that comprises a memory device storinginstructions, and a processing device communicatively coupled to thememory device. The processing device executes the instructions to:receive user data obtained from records associated with a user; generatea modified treatment plan based on the user data; and send, to atreatment apparatus accessible to the user, the modified treatment plan,wherein the modified treatment plan causes the treatment apparatus toupdate at least one operational aspect of the treatment apparatus, andupdate at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.

In one embodiment, a method includes receiving user data obtained fromelectronic or physical records associated with a user. The methodincludes generating a modified treatment plan based on the user data.The method further includes sending, to a treatment apparatus accessibleto the user, the modified treatment plan, wherein the modified treatmentplan causes the treatment apparatus to: update at least one operationalaspect of the treatment apparatus, and update at least one operationalaspect of at least one other device communicatively coupled to thetreatment apparatus.

In one embodiment, a tangible, non-transitory computer-readable mediumstores instructions that, when executed, cause a processing device toperform any of the methods, operations, or steps described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

For a detailed description of example embodiments, reference will now bemade to the accompanying drawings in which:

FIG. 1 shows a block diagram of an embodiment of a computer implementedsystem for managing a treatment plan according to the presentdisclosure;

FIG. 2 shows a perspective view of an embodiment of a treatmentapparatus according to the present disclosure;

FIG. 3 shows a perspective view of a pedal of the treatment apparatus ofFIG. 2 according to the present disclosure;

FIG. 4 shows a perspective view of a person using the treatmentapparatus of FIG. 2 according to the present disclosure;

FIG. 5 shows an example embodiment of an overview display of anassistant interface according to the present disclosure;

FIG. 6 shows an example block diagram of training a machine learningmodel to output, based on data pertaining to the patient, a treatmentplan for the patient according to the present disclosure;

FIG. 7 illustrates a block diagram of a system for implementing dynamictreatment environments based on patient information, according to someembodiments;

FIGS. 8A-8H illustrate conceptual diagrams for implementing a dynamictreatment environment based on a patient's information, according tosome embodiments;

FIG. 9 shows an example embodiment of a method for implementing dynamictreatment environments, according to some embodiments;

FIG. 10 shows an example embodiment of another method for implementingdynamic treatment environments, according to some embodiments; and

FIG. 11 shows an example computer system according to the presentdisclosure.

NOTATION AND NOMENCLATURE

Various terms are used to refer to particular system components.Different companies may refer to a component by different names—thisdocument does not intend to distinguish between components that differin name but not function. In the following discussion and in the claims,the terms “including” and “comprising” are used in an open-endedfashion, and thus should be interpreted to mean “including, but notlimited to . . . .” Also, the term “couple” or “couples” is intended tomean either an indirect or direct connection. Thus, if a first devicecouples to a second device, that connection may be through a directconnection or through an indirect connection via other devices andconnections.

The terminology used herein is for the purpose of describing particularexample embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. The method steps, processes, and operations described hereinare not to be construed as necessarily requiring their performance inthe particular order discussed or illustrated, unless specificallyidentified as an order of performance. It is also to be understood thatadditional or alternative steps may be employed.

The terms first, second, third, etc. may be used herein to describevarious elements, components, regions, layers and/or sections; however,these elements, components, regions, layers and/or sections should notbe limited by these terms. These terms may be only used to distinguishone element, component, region, layer, or section from another region,layer, or section. Terms such as “first,” “second,” and other numericalterms, when used herein, do not imply a sequence or order unless clearlyindicated by the context. Thus, a first element, component, region,layer, or section discussed below could be termed a second element,component, region, layer, or section without departing from theteachings of the example embodiments. The phrase “at least one of,” whenused with a list of items, means that different combinations of one ormore of the listed items may be used, and only one item in the list maybe needed. For example, “at least one of: A, B, and C” includes any ofthe following combinations: A, B, C, A and B, A and C, B and C, and Aand B and C. In another example, the phrase “one or more” when used witha list of items means there may be one item or any suitable number ofitems exceeding one.

Spatially relative terms, such as “inner,” “outer,” “beneath,” “below,”“lower,” “above,” “upper,” “top,” “bottom,” and the like, may be usedherein. These spatially relative terms can be used for ease ofdescription to describe one element's or feature's relationship toanother element(s) or feature(s) as illustrated in the figures. Thespatially relative terms may also be intended to encompass differentorientations of the device in use, or operation, in addition to theorientation depicted in the figures. For example, if the device in thefigures is turned over, elements described as “below” or “beneath” otherelements or features would then be oriented “above” the other elementsor features. Thus, the example term “below” can encompass both anorientation of above and below. The device may be otherwise oriented(rotated 90 degrees or at other orientations) and the spatially relativedescriptions used herein interpreted accordingly.

A “treatment plan” may include one or more treatment protocols, and eachtreatment protocol includes one or more treatment sessions. Eachtreatment session comprises several session periods, with each sessionperiod including a particular exercise for treating the body part of thepatient. For example, a treatment plan for post-operative rehabilitationafter a knee surgery may include an initial treatment protocol withtwice daily stretching sessions for the first 3 days after surgery and amore intensive treatment protocol with active exercise sessionsperformed 4 times per day starting 4 days after surgery. A treatmentplan may also include information pertaining to a medical procedure toperform on the patient, a treatment protocol for the patient using atreatment apparatus, a diet regimen for the patient, a medicationregimen for the patient, a sleep regimen for the patient, additionalregimens, or some combination thereof.

The terms telemedicine, telehealth, telemed, teletherapeutic, etc. maybe used interchangeably herein.

DETAILED DESCRIPTION

The following discussion is directed to various embodiments of thepresent disclosure. Although one or more of these embodiments may bepreferred, the embodiments disclosed should not be interpreted, orotherwise used, as limiting the scope of the disclosure, including theclaims. In addition, one skilled in the art will understand that thefollowing description has broad application, and the discussion of anyembodiment is meant only to be exemplary of that embodiment, and notintended to intimate that the scope of the disclosure, including theclaims, is limited to that embodiment.

Determining a treatment plan for a patient having certaincharacteristics (e.g., vital-sign or other measurements; performance;demographic; geographic; diagnostic; measurement- or test-based;medically historic; etiologic; cohort-associative; differentiallydiagnostic; surgical, physically therapeutic, pharmacologic, and othertreatment(s) recommended; etc.) may be a technically challengingproblem. For example, a multitude of information may be considered whendetermining a treatment plan, which may result in inefficiencies andinaccuracies in the treatment plan selection process. In arehabilitative setting, some of the multitude of information consideredmay include characteristics of the patient such as personal information,performance information, and measurement information. The personalinformation may include, e.g., demographic, psychographic or otherinformation, such as an age, a weight, a gender, a height, a body massindex, a medical condition, a familial medication history, an injury, amedical procedure, a medication prescribed, or some combination thereof.The performance information may include, e.g., an elapsed time of usinga treatment apparatus, an amount of force exerted on a portion of thetreatment apparatus, a range of motion achieved on the treatmentapparatus, a movement speed of a portion of the treatment apparatus, anindication of a plurality of pain levels using the treatment apparatus,or some combination thereof. The measurement information may include,e.g., a vital sign, a respiration rate, a heartrate, a temperature, ablood pressure, or some combination thereof. It may be desirable toprocess the characteristics of a multitude of patients, the treatmentplans performed for those patients, and the results of the treatmentplans for those patients.

Further, another technical problem may involve distally treating, via acomputing device during a telemedicine or telehealth session, a patientfrom a location different than a location at which the patient islocated. An additional technical problem is controlling or enabling thecontrol of, from the different location, a treatment apparatus used bythe patient at the location at which the patient is located. Oftentimes,when a patient undergoes rehabilitative surgery (e.g., knee surgery), aphysical therapist or other medical professional may prescribe atreatment apparatus to the patient to use to perform a treatmentprotocol at their residence or any mobile location or temporarydomicile. A medical professional may refer to a doctor, physicianassistant, nurse, chiropractor, dentist, physical therapist,acupuncturist, physical trainer, or the like. A medical professional mayrefer to any person with a credential, license, degree, or the like inthe field of medicine, physical therapy, rehabilitation, or the like.

Since the physical therapist or other medical professional is located ina different location from the patient and the treatment apparatus, itmay be technically challenging for the physical therapist or othermedical professional to monitor the patient's actual progress (asopposed to relying on the patient's word about their progress) using thetreatment apparatus, modify the treatment plan according to thepatient's progress, adapt the treatment apparatus to the personalcharacteristics of the patient as the patient performs the treatmentplan, and the like.

Accordingly, some embodiments of the present disclosure pertain to usingartificial intelligence and/or machine learning to assign patients tocohorts and to dynamically control a treatment apparatus based on theassignment during an adaptive telemedical session. In some embodiments,numerous treatment apparatuses may be provided to patients. Thetreatment apparatuses may be used by the patients to perform treatmentplans in their residences, at a gym, at a rehabilitative center, at ahospital, or any suitable location, including permanent or temporarydomiciles. In some embodiments, the treatment apparatuses may becommunicatively coupled to a server. Characteristics of the patients maybe collected before, during, and/or after the patients perform thetreatment plans. For example, the personal information, the performanceinformation, and the measurement information may be collected before,during, and/or after the person performs the treatment plans. Theresults (e.g., improved performance or decreased performance) ofperforming each exercise may be collected from the treatment apparatusthroughout the treatment plan and after the treatment plan is performed.The parameters, settings, configurations, etc. (e.g., position of pedal,amount of resistance, etc.) of the treatment apparatus may be collectedbefore, during, and/or after the treatment plan is performed.

Each characteristic of the patient, each result, and each parameter,setting, configuration, etc. may be timestamped and may be correlatedwith a particular step in the treatment plan. Such a technique mayenable determining which steps in the treatment plan led to desiredresults (e.g., improved muscle strength, range of motion, etc.) andwhich steps lead to diminishing returns (e.g., continuing to exerciseafter 3 minutes actually delays or harms recovery).

Data may be collected from the treatment apparatuses and/or any suitablecomputing device (e.g., computing devices where personal information isentered, such as a clinician interface or patient interface) over timeas the patients use the treatment apparatuses to perform the varioustreatment plans. The data that may be collected may include thecharacteristics of the patients, the treatment plans performed by thepatients, and the results of the treatment plans.

In some embodiments, the data may be processed to group certain peopleinto cohorts. The people may be grouped by people having certain orselected similar characteristics, treatment plans, and results ofperforming the treatment plans. For example, athletic people having nomedical conditions who perform a treatment plan (e.g., use the treatmentapparatus for 30 minutes a day 5 times a week for 3 weeks) and who fullyrecover may be grouped into a first cohort. Older people who areclassified obese and who perform a treatment plan (e.g., use thetreatment plan for 10 minutes a day 3 times a week for 4 weeks) and whoimprove their range of motion by 75 percent may be grouped into a secondcohort.

In some embodiments, an artificial intelligence engine may include oneor more machine learning models that are trained using the cohorts. Forexample, the one or more machine learning models may be trained toreceive an input of characteristics of a new patient and to output atreatment plan for the patient that results in a desired result. Themachine learning models may match a pattern between the characteristicsof the new patient and at least one patient of the patients included ina particular cohort. When a pattern is matched, the machine learningmodels may assign the new patient to the particular cohort and selectthe treatment plan associated with the at least one patient. Theartificial intelligence engine may be configured to control, distallyand based on the treatment plan, the treatment apparatus while the newpatient uses the treatment apparatus to perform the treatment plan.

As may be appreciated, the characteristics of the new patient may changeas the new patient uses the treatment apparatus to perform the treatmentplan. For example, the performance of the patient may improve quickerthan expected for people in the cohort to which the new patient iscurrently assigned. Accordingly, the machine learning models may betrained to dynamically reassign, based on the changed characteristics,the new patient to a different cohort that includes people havingcharacteristics similar to the now-changed characteristics as the newpatient. For example, a clinically obese patient may lose weight and nolonger meet the weight criterion for the initial cohort, result in thepatient's being reassigned to a different cohort with a different weightcriterion. A different treatment plan may be selected for the newpatient, and the treatment apparatus may be controlled, distally andbased on the different treatment plan, the treatment apparatus while thenew patient uses the treatment apparatus to perform the treatment plan.Such techniques may provide the technical solution of distallycontrolling a treatment apparatus. Further, the techniques may lead tofaster recovery times and/or better results for the patients because thetreatment plan that most accurately fits their characteristics isselected and implemented, in real-time, at any given moment. “Real-time”may also refer to near real-time, which may be less than 10 seconds. Asdescribed herein, the term “results” may refer to medical results ormedical outcomes. Results and outcomes may refer to responses to medicalactions.

Depending on what result is desired, the artificial intelligence enginemay be trained to output several treatment plans. For example, oneresult may include recovering to a threshold level (e.g., 75% range ofmotion) in a fastest amount of time, while another result may includefully recovering (e.g., 100% range of motion) regardless of the amountof time. The data obtained from the patients and sorted into cohorts mayindicate that a first treatment plan provides the first result forpeople with characteristics similar to the patient's, and that a secondtreatment plan provides the second result for people withcharacteristics similar to the patient.

Further, the artificial intelligence engine may also be trained tooutput treatment plans that are not optimal or sub-optimal or eveninappropriate (all referred to, without limitation, as “excludedtreatment plans”) for the patient. For example, if a patient has highblood pressure, a particular exercise may not be approved or suitablefor the patient as it may put the patient at unnecessary risk or eveninduce a hypertensive crisis and, accordingly, that exercise may beflagged in the excluded treatment plan for the patient.

In some embodiments, the treatment plans and/or excluded treatment plansmay be presented, during a telemedicine or telehealth session, to amedical professional. The medical professional may select a particulartreatment plan for the patient to cause that treatment plan to betransmitted to the patient and/or to control, based on the treatmentplan, the treatment apparatus. In some embodiments, to facilitatetelehealth or telemedicine applications, including remote diagnoses,determination of treatment plans and rehabilitative and/or pharmacologicprescriptions, the artificial intelligence engine may receive and/oroperate distally from the patient and the treatment apparatus. In suchcases, the recommended treatment plans and/or excluded treatment plansmay be presented simultaneously with a video of the patient in real-timeor near real-time during a telemedicine or telehealth session on a userinterface of a computing device of a medical professional. The video mayalso be accompanied by audio, text, and other multimedia information.Real-time may refer to less than or equal to 2 seconds. Near real-timemay refer to any interaction of a sufficiently short time to enable twoindividuals to engage in a dialogue via such user interface and willgenerally be less than 10 seconds but greater than 2 seconds.

Presenting the treatment plans generated by the artificial intelligenceengine concurrently with a presentation of the patient video may providean enhanced user interface because the medical professional may continueto visually and/or otherwise communicate with the patient while alsoreviewing the treatment plans on the same user interface. The enhanceduser interface may improve the medical professional's experience usingthe computing device and may encourage the medical professional to reusethe user interface. Such a technique may also reduce computing resources(e.g., processing, memory, network) because the medical professionaldoes not have to switch to another user interface screen to enter aquery for a treatment plan to recommend based on the characteristics ofthe patient. The artificial intelligence engine provides, dynamically onthe fly, the treatment plans and excluded treatment plans.

In some embodiments, the treatment apparatus may be adaptive and/orpersonalized because its properties, configurations, and positions maybe adapted to the needs of a particular patient. For example, the pedalsmay be dynamically adjusted on the fly (e.g., via a telemedicine sessionor based on programmed configurations in response to certainmeasurements being detected) to increase or decrease a range of motionto comply with a treatment plan designed for the user. In someembodiments, a medical professional may adapt, remotely during atelemedicine session, the treatment apparatus to the needs of thepatient by causing a control instruction to be transmitted from a serverto treatment apparatus. Such adaptive nature may improve the results ofrecovery for a patient, furthering the goals of personalized medicine,and enabling personalization of the treatment plan on a per-individualbasis.

FIG. 1 shows a block diagram of a computer-implemented system 10,hereinafter called “the system” for managing a treatment plan. Managingthe treatment plan may include using an artificial intelligence engineto recommend treatment plans and/or provide excluded treatment plansthat should not be recommended to a patient.

The system 10 also includes a server 30 configured to store and toprovide data related to managing the treatment plan. The server 30 mayinclude one or more computers and may take the form of a distributedand/or virtualized computer or computers. The server 30 also includes afirst communication interface 32 configured to communicate with theclinician interface 20 via a first network 34. In some embodiments, thefirst network 34 may include wired and/or wireless network connectionssuch as Wi-Fi, Bluetooth, ZigBee, Near-Field Communications (NFC),cellular data network, etc. The server 30 includes a first processor 36and a first machine-readable storage memory 38, which may be called a“memory” for short, holding first instructions 40 for performing thevarious actions of the server 30 for execution by the first processor36. The server 30 is configured to store data regarding the treatmentplan. For example, the memory 38 includes a system data store 42configured to hold system data, such as data pertaining to treatmentplans for treating one or more patients. The server 30 is alsoconfigured to store data regarding performance by a patient in followinga treatment plan. For example, the memory 38 includes a patient datastore 44 configured to hold patient data, such as data pertaining to theone or more patients, including data representing each patient'sperformance within the treatment plan.

According to some embodiments, all or a portion of the data describedthroughout this disclosure can be stored on/provided by a data source 15with which the server 30 is communicably coupled. Moreover, the datasource 15 can store patient data that can be retrieved and utilized bythe server 30. For example, the data source 15 can provide access todata obtained from electronic medical records systems, insuranceprovider systems, and the like.

In addition, the characteristics (e.g., personal, performance,measurement, etc.) of the people, the treatment plans followed by thepeople, the level of compliance with the treatment plans, and theresults of the treatment plans may use correlations and otherstatistical or probabilistic measures to enable the partitioning of orto partition the treatment plans into different patientcohort-equivalent databases in the patient data store 44. For example,the data for a first cohort of first patients having a first similarinjury, a first similar medical condition, a first similar medicalprocedure performed, a first treatment plan followed by the firstpatient, and a first result of the treatment plan may be stored in afirst patient database. The data for a second cohort of second patientshaving a second similar injury, a second similar medical condition, asecond similar medical procedure performed, a second treatment planfollowed by the second patient, and a second result of the treatmentplan may be stored in a second patient database. Any singlecharacteristic or any combination of characteristics may be used toseparate the cohorts of patients. In some embodiments, the differentcohorts of patients may be stored in different partitions or volumes ofthe same database. There is no specific limit to the number of differentcohorts of patients allowed, other than as limited by mathematicalcombinatoric and/or partition theory.

This characteristic data, treatment plan data, and results data may beobtained from numerous treatment apparatuses and/or computing devicesover time and stored in the database 44. The characteristic data,treatment plan data, and results data may be correlated in thepatient-cohort databases in the patient data store 44. Thecharacteristics of the people may include personal information,performance information, and/or measurement information.

In addition to the historical information about other people stored inthe patient cohort-equivalent databases, real-time or near-real-timeinformation based on the current patient's characteristics about acurrent patient being treated may be stored in an appropriate patientcohort-equivalent database. The characteristics of the patient may bedetermined to match or be similar to the characteristics of anotherperson in a particular cohort (e.g., cohort A) and the patient may beassigned to that cohort.

In some embodiments, the server 30 may execute an artificialintelligence (Al) engine 11 that uses one or more machine learningmodels 13 to perform at least one of the embodiments disclosed herein.The server 30 may include a training engine 9 capable of generating theone or more machine learning models 13. The machine learning models 13may be trained to assign people to certain cohorts based on theircharacteristics, select treatment plans using real-time and historicaldata correlations involving patient cohort-equivalents, and control atreatment apparatus 70, among other things. The one or more machinelearning models 13 may be generated by the training engine 9 and may beimplemented in computer instructions executable by one or moreprocessing devices of the training engine 9 and/or the servers 30. Togenerate the one or more machine learning models 13, the training engine9 may train the one or more machine learning models 13. The one or moremachine learning models 13 may be used by the artificial intelligenceengine 11.

The training engine 9 may be a rackmount server, a router computer, apersonal computer, a portable digital assistant, a smartphone, a laptopcomputer, a tablet computer, a netbook, a desktop computer, an Internetof Things (IoT) device, any other desired computing device, or anycombination of the above. The training engine 9 may be cloud-based or areal-time software platform, and it may include privacy software orprotocols, and/or security software or protocols.

To train the one or more machine learning models 13, the training engine9 may use a training data set of a corpus of the characteristics of thepeople that used the treatment apparatus 70 to perform treatment plans,the details (e.g., treatment protocol including exercises, amount oftime to perform the exercises, how often to perform the exercises, aschedule of exercises, parameters/configurations/settings of thetreatment apparatus 70 throughout each step of the treatment plan, etc.)of the treatment plans performed by the people using the treatmentapparatus 70, and the results of the treatment plans performed by thepeople. The one or more machine learning models 13 may be trained tomatch patterns of characteristics of a patient with characteristics ofother people in assigned to a particular cohort. The term “match” mayrefer to an exact match, a correlative match, a substantial match, etc.The one or more machine learning models 13 may be trained to receive thecharacteristics of a patient as input, map the characteristics tocharacteristics of people assigned to a cohort, and select a treatmentplan from that cohort. The one or more machine learning models 13 mayalso be trained to control, based on the treatment plan, the machinelearning apparatus 70.

Different machine learning models 13 may be trained to recommenddifferent treatment plans for different desired results. For example,one machine learning model may be trained to recommend treatment plansfor most effective recovery, while another machine learning model may betrained to recommend treatment plans based on speed of recovery.

Using training data that includes training inputs and correspondingtarget outputs, the one or more machine learning models 13 may refer tomodel artifacts created by the training engine 9. The training engine 9may find patterns in the training data wherein such patterns map thetraining input to the target output and generate the machine learningmodels 13 that capture these patterns. In some embodiments, theartificial intelligence engine 11, the system data store 42/patient datastore 44, and/or the training engine 9 may reside on another component(e.g., assistant interface 94, clinician interface 20, etc.) depicted inFIG. 1.

The one or more machine learning models 13 may comprise, e.g., a singlelevel of linear or non-linear operations (e.g., a support vector machine[SVM]) or the machine learning models 13 may be a deep network, i.e., amachine learning model comprising multiple levels of non-linearoperations. Examples of deep networks are neural networks includinggenerative adversarial networks, convolutional neural networks,recurrent neural networks with one or more hidden layers, and fullyconnected neural networks (e.g., each neuron may transmit its outputsignal to the input of the remaining neurons, as well as to itself). Forexample, the machine learning model may include numerous layers and/orhidden layers that perform calculations (e.g., dot products) usingvarious neurons.

The system 10 also includes a patient interface 50 configured tocommunicate information to a patient and to receive feedback from thepatient. Specifically, the patient interface includes an input device 52and an output device 54, which may be collectively called a patient userinterface 52, 54. The input device 52 may include one or more devices,such as a keyboard, a mouse, a touch screen input, a gesture sensor,and/or a microphone and processor configured for voice recognition. Theoutput device 54 may take one or more different forms including, forexample, a computer monitor or display screen on a tablet, smartphone,or a smart watch. The output device 54 may include other hardware and/orsoftware components such as a projector, virtual reality capability,augmented reality capability, etc. The output device 54 may incorporatevarious different visual, audio, or other presentation technologies. Forexample, the output device 54 may include a non-visual display, such asan audio signal, which may include spoken language and/or other soundssuch as tones, chimes, and/or melodies, which may signal differentconditions and/or directions. The output device 54 may comprise one ormore different display screens presenting various data and/or interfacesor controls for use by the patient. The output device 54 may includegraphics, which may be presented by a web-based interface and/or by acomputer program or application (App.).

As shown in FIG. 1, the patient interface 50 includes a secondcommunication interface 56, which may also be called a remotecommunication interface configured to communicate with the server 30and/or the clinician interface 20 via a second network 58. In someembodiments, the second network 58 may include a local area network(LAN), such as an Ethernet network. In some embodiments, the secondnetwork 58 may include the Internet, and communications between thepatient interface 50 and the server 30 and/or the clinician interface 20may be secured via encryption, such as, for example, by using a virtualprivate network (VPN). In some embodiments, the second network 58 mayinclude wired and/or wireless network connections such as Wi-Fi,Bluetooth, ZigBee, Near-Field Communications (NFC), cellular datanetwork, etc. In some embodiments, the second network 58 may be the sameas and/or operationally coupled to the first network 34.

The patient interface 50 includes a second processor 60 and a secondmachine-readable storage memory 62 holding second instructions 64 forexecution by the second processor 60 for performing various actions ofpatient interface 50. The second machine-readable storage memory 62 alsoincludes a local data store 66 configured to hold data, such as datapertaining to a treatment plan and/or patient data, such as datarepresenting a patient's performance within a treatment plan. Thepatient interface 50 also includes a local communication interface 68configured to communicate with various devices for use by the patient inthe vicinity of the patient interface 50. The local communicationinterface 68 may include wired and/or wireless communications. In someembodiments, the local communication interface 68 may include a localwireless network such as Wi-Fi, Bluetooth, ZigBee, Near-FieldCommunications (NFC), cellular data network, etc.

The system 10 also includes a treatment apparatus 70 configured to bemanipulated by the patient and/or to manipulate a body part of thepatient for performing activities according to the treatment plan. Insome embodiments, the treatment apparatus 70 may take the form of anexercise and rehabilitation apparatus configured to perform and/or toaid in the performance of a rehabilitation regimen, which may be anorthopedic rehabilitation regimen, and the treatment includesrehabilitation of a body part of the patient, such as a joint or a boneor a muscle group. The treatment apparatus 70 may be any suitablemedical, rehabilitative, therapeutic, etc. apparatus configured to becontrolled distally via another computing device to treat a patientand/or exercise the patient. The treatment apparatus 70 may be anelectromechanical machine including one or more weights, anelectromechanical bicycle, an electromechanical spin-wheel, asmart-mirror, a treadmill, or the like. The body part may include, forexample, a spine, a hand, a foot, a knee, or a shoulder. The body partmay include a part of a joint, a bone, or a muscle group, such as one ormore vertebrae, a tendon, or a ligament. As shown in FIG. 1, thetreatment apparatus 70 includes a controller 72, which may include oneor more processors, computer memory, and/or other components. Thetreatment apparatus 70 also includes a fourth communication interface 74configured to communicate with the patient interface 50 via the localcommunication interface 68. The treatment apparatus 70 also includes oneor more internal sensors 76 and an actuator 78, such as a motor. Theactuator 78 may be used, for example, for moving the patient's body partand/or for resisting forces by the patient.

The internal sensors 76 may measure one or more operatingcharacteristics of the treatment apparatus 70 such as, for example, aforce a position, a speed, and/or a velocity. In some embodiments, theinternal sensors 76 may include a position sensor configured to measureat least one of a linear motion or an angular motion of a body part ofthe patient. For example, an internal sensor 76 in the form of aposition sensor may measure a distance that the patient is able to movea part of the treatment apparatus 70, where such distance may correspondto a range of motion that the patient's body part is able to achieve. Insome embodiments, the internal sensors 76 may include a force sensorconfigured to measure a force applied by the patient. For example, aninternal sensor 76 in the form of a force sensor may measure a force orweight the patient is able to apply, using a particular body part, tothe treatment apparatus 70.

The system 10 shown in FIG. 1 also includes an ambulation sensor 82,which communicates with the server 30 via the local communicationinterface 68 of the patient interface 50. The ambulation sensor 82 maytrack and store a number of steps taken by the patient. In someembodiments, the ambulation sensor 82 may take the form of a wristband,wristwatch, or smart watch. In some embodiments, the ambulation sensor82 may be integrated within a phone, such as a smartphone.

The system 10 shown in FIG. 1 also includes a goniometer 84, whichcommunicates with the server 30 via the local communication interface 68of the patient interface 50. The goniometer 84 measures an angle of thepatient's body part. For example, the goniometer 84 may measure theangle of flex of a patient's knee or elbow or shoulder.

The system 10 shown in FIG. 1 also includes a pressure sensor 86, whichcommunicates with the server 30 via the local communication interface 68of the patient interface 50. The pressure sensor 86 measures an amountof pressure or weight applied by a body part of the patient. Forexample, pressure sensor 86 may measure an amount of force applied by apatient's foot when pedaling a stationary bike.

The system 10 shown in FIG. 1 also includes a supervisory interface 90which may be similar or identical to the clinician interface 20. In someembodiments, the supervisory interface 90 may have enhancedfunctionality beyond what is provided on the clinician interface 20. Thesupervisory interface 90 may be configured for use by a person havingresponsibility for the treatment plan, such as an orthopedic surgeon.

The system 10 shown in FIG. 1 also includes a reporting interface 92which may be similar or identical to the clinician interface 20. In someembodiments, the reporting interface 92 may have less functionality fromwhat is provided on the clinician interface 20. For example, thereporting interface 92 may not have the ability to modify a treatmentplan. Such a reporting interface 92 may be used, for example, by abiller to determine the use of the system 10 for billing purposes. Inanother example, the reporting interface 92 may not have the ability todisplay patient identifiable information, presenting only pseudonymizeddata and/or anonymized data for certain data fields concerning a datasubject and/or for certain data fields concerning a quasi-identifier ofthe data subject. Such a reporting interface 92 may be used, forexample, by a researcher to determine various effects of a treatmentplan on different patients.

The system 10 includes an assistant interface 94 for an assistant, suchas a doctor, a nurse, a physical therapist, or a technician, to remotelycommunicate with the patient interface 50 and/or the treatment apparatus70. Such remote communications may enable the assistant to assist orguide a patient using the system 10. More specifically, the assistantinterface 94 is configured to communicate a telemedicine signal 96, 97,98 a, 98 b, 99 a, 99 b with the patient interface 50 via a networkconnection such as, for example, via the first network 34 and/or thesecond network 58. The telemedicine signal 96, 97, 98 a, 98 b, 99 a, 99b comprises one of an audio signal 96, an audiovisual signal 97, aninterface control signal 98 a for controlling a function of the patientinterface 50, an interface monitor signal 98 b for monitoring a statusof the patient interface 50, an apparatus control signal 99 a forchanging an operating parameter of the treatment apparatus 70, and/or anapparatus monitor signal 99 b for monitoring a status of the treatmentapparatus 70. In some embodiments, each of the control signals 98 a, 99a may be unidirectional, conveying commands from the assistant interface94 to the patient interface 50. In some embodiments, in response tosuccessfully receiving a control signal 98 a, 99 a and/or to communicatesuccessful and/or unsuccessful implementation of the requested controlaction, an acknowledgement message may be sent from the patientinterface 50 to the assistant interface 94. In some embodiments, each ofthe monitor signals 98 b, 99 b may be unidirectional, status-informationcommands from the patient interface 50 to the assistant interface 94. Insome embodiments, an acknowledgement message may be sent from theassistant interface 94 to the patient interface 50 in response tosuccessfully receiving one of the monitor signals 98 b, 99 b.

In some embodiments, the patient interface 50 may be configured as apass-through for the apparatus control signals 99 a and the apparatusmonitor signals 99 b between the treatment apparatus 70 and one or moreother devices, such as the assistant interface 94 and/or the server 30.For example, the patient interface 50 may be configured to transmit anapparatus control signal 99 a in response to an apparatus control signal99 a within the telemedicine signal 96, 97, 98 a, 98 b, 99 a, 99 b fromthe assistant interface 94.

In some embodiments, the assistant interface 94 may be presented on ashared physical device as the clinician interface 20. For example, theclinician interface 20 may include one or more screens that implementthe assistant interface 94. Alternatively, or additionally, theclinician interface 20 may include additional hardware components, suchas a video camera, a speaker, and/or a microphone, to implement aspectsof the assistant interface 94.

In some embodiments, one or more portions of the telemedicine signal 96,97, 98 a, 98 b, 99 a, 99 b may be generated from a prerecorded source(e.g., an audio recording, a video recording, or an animation) forpresentation by the output device 54 of the patient interface 50. Forexample, a tutorial video may be streamed from the server 30 andpresented upon the patient interface 50. Content from the prerecordedsource may be requested by the patient via the patient interface 50.Alternatively, via a control on the assistant interface 94, theassistant may cause content from the prerecorded source to be played onthe patient interface 50.

The assistant interface 94 includes an assistant input device 22 and anassistant display 24, which may be collectively called an assistant userinterface 22, 24. The assistant input device 22 may include one or moreof a telephone, a keyboard, a mouse, a trackpad, or a touch screen, forexample. Alternatively, or additionally, the assistant input device 22may include one or more microphones. In some embodiments, the one ormore microphones may take the form of a telephone handset, headset, orwide-area microphone or microphones configured for the assistant tospeak to a patient via the patient interface 50. In some embodiments,assistant input device 22 may be configured to provide voice-basedfunctionalities, with hardware and/or software configured to interpretspoken instructions by the assistant by using the one or moremicrophones. The assistant input device 22 may include functionalityprovided by or similar to existing voice-based assistants such as Siriby Apple, Alexa by Amazon, Google Assistant, or Bixby by Samsung. Theassistant input device 22 may include other hardware and/or softwarecomponents. The assistant input device 22 may include one or moregeneral purpose devices and/or special-purpose devices.

The assistant display 24 may take one or more different forms including,for example, a computer monitor or display screen on a tablet, asmartphone, or a smart watch. The assistant display 24 may include otherhardware and/or software components such as projectors, virtual realitycapabilities, or augmented reality capabilities, etc. The assistantdisplay 24 may incorporate various different visual, audio, or otherpresentation technologies. For example, the assistant display 24 mayinclude a non-visual display, such as an audio signal, which may includespoken language and/or other sounds such as tones, chimes, melodies,and/or compositions, which may signal different conditions and/ordirections. The assistant display 24 may comprise one or more differentdisplay screens presenting various data and/or interfaces or controlsfor use by the assistant. The assistant display 24 may include graphics,which may be presented by a web-based interface and/or by a computerprogram or application (App.).

In some embodiments, the system 10 may provide computer translation oflanguage from the assistant interface 94 to the patient interface 50and/or vice-versa. The computer translation of language may includecomputer translation of spoken language and/or computer translation oftext. Additionally, or alternatively, the system 10 may provide voicerecognition and/or spoken pronunciation of text. For example, the system10 may convert spoken words to printed text and/or the system 10 mayaudibly speak language from printed text. The system 10 may beconfigured to recognize spoken words by any or all of the patient, theclinician, and/or the assistant. In some embodiments, the system 10 maybe configured to recognize and react to spoken requests or commands bythe patient. For example, the system 10 may automatically initiate atelemedicine session in response to a verbal command by the patient(which may be given in any one of several different languages).

In some embodiments, the server 30 may generate aspects of the assistantdisplay 24 for presentation by the assistant interface 94. For example,the server 30 may include a web server configured to generate thedisplay screens for presentation upon the assistant display 24. Forexample, the artificial intelligence engine 11 may generate recommendedtreatment plans and/or excluded treatment plans for patients andgenerate the display screens including those recommended treatment plansand/or external treatment plans for presentation on the assistantdisplay 24 of the assistant interface 94. In some embodiments, theassistant display 24 may be configured to present a virtualized desktophosted by the server 30. In some embodiments, the server 30 may beconfigured to communicate with the assistant interface 94 via the firstnetwork 34. In some embodiments, the first network 34 may include alocal area network (LAN), such as an Ethernet network. In someembodiments, the first network 34 may include the Internet, andcommunications between the server 30 and the assistant interface 94 maybe secured via privacy enhancing technologies, such as, for example, byusing encryption over a virtual private network (VPN). Alternatively, oradditionally, the server 30 may be configured to communicate with theassistant interface 94 via one or more networks independent of the firstnetwork 34 and/or other communication means, such as a direct wired orwireless communication channel. In some embodiments, the patientinterface 50 and the treatment apparatus 70 may each operate from apatient location geographically separate from a location of theassistant interface 94. For example, the patient interface 50 and thetreatment apparatus 70 may be used as part of an in-home rehabilitationsystem, which may be aided remotely by using the assistant interface 94at a centralized location, such as a clinic or a call center.

In some embodiments, the assistant interface 94 may be one of severaldifferent terminals (e.g., computing devices) that may be groupedtogether, for example, in one or more call centers or at one or moreclinicians' offices. In some embodiments, a plurality of assistantinterfaces 94 may be distributed geographically. In some embodiments, aperson may work as an assistant remotely from any conventional officeinfrastructure. Such remote work may be performed, for example, wherethe assistant interface 94 takes the form of a computer and/ortelephone. This remote work functionality may allow for work-from-homearrangements that may include part time and/or flexible work hours foran assistant.

FIGS. 2-3 show an embodiment of a treatment apparatus 70. Morespecifically, FIG. 2 shows a treatment apparatus 70 in the form of astationary cycling machine 100, which may be called a stationary bike,for short. The stationary cycling machine 100 includes a set of pedals102 each attached to a pedal arm 104 for rotation about an axle 106. Insome embodiments, and as shown in FIG. 2, the pedals 102 are movable onthe pedal arms 104 in order to adjust a range of motion used by thepatient in pedaling. For example, the pedals being located inwardlytoward the axle 106 corresponds to a smaller range of motion than whenthe pedals are located outwardly away from the axle 106. A pressuresensor 86 is attached to or embedded within one of the pedals 102 formeasuring an amount of force applied by the patient on the pedal 102.The pressure sensor 86 may communicate wirelessly to the treatmentapparatus 70 and/or to the patient interface 50.

FIG. 4 shows a person (a patient) using the treatment apparatus of FIG.2 and shows sensors and various data parameters connected to a patientinterface 50. The example patient interface 50 is a tablet computer orsmartphone, or a phablet, such as an iPad, an iPhone, an Android device,or a Surface tablet, which is held manually by the patient. In someother embodiments, the patient interface 50 may be embedded within orattached to the treatment apparatus 70. FIG. 4 shows the patient wearingthe ambulation sensor 82 on his wrist, with a note showing “STEPS TODAY1355”, indicating that the ambulation sensor 82 has recorded andtransmitted that step count to the patient interface 50. FIG. 4 alsoshows the patient wearing the goniometer 84 on his right knee, with anote showing “KNEE ANGLE 72°”, indicating that the goniometer 84 ismeasuring and transmitting that knee angle to the patient interface 50.FIG. 4 also shows a right side of one of the pedals 102 with a pressuresensor 86 showing “FORCE 12.5 lbs.,” indicating that the right pedalpressure sensor 86 is measuring and transmitting that force measurementto the patient interface 50. FIG. 4 also shows a left side of one of thepedals 102 with a pressure sensor 86 showing “FORCE 27 lbs.”, indicatingthat the left pedal pressure sensor 86 is measuring and transmittingthat force measurement to the patient interface 50. FIG. 4 also showsother patient data, such as an indicator of “SESSION TIME 0:04:13”,indicating that the patient has been using the treatment apparatus 70for 4 minutes and 13 seconds. This session time may be determined by thepatient interface 50 based on information received from the treatmentapparatus 70. FIG. 4 also shows an indicator showing “PAIN LEVEL 3”.Such a pain level may be obtained from the patent in response to asolicitation, such as a question, presented upon the patient interface50.

FIG. 5 is an example embodiment of an overview display 120 of theassistant interface 94. Specifically, the overview display 120 presentsseveral different controls and interfaces for the assistant to remotelyassist a patient with using the patient interface 50 and/or thetreatment apparatus 70. This remote assistance functionality may also becalled telemedicine or telehealth.

Specifically, the overview display 120 includes a patient profiledisplay 130 presenting biographical information regarding a patientusing the treatment apparatus 70. The patient profile display 130 maytake the form of a portion or region of the overview display 120, asshown in FIG. 5, although the patient profile display 130 may take otherforms, such as a separate screen or a popup window. In some embodiments,the patient profile display 130 may include a limited subset of thepatient's biographical information. More specifically, the datapresented upon the patient profile display 130 may depend upon theassistant's need for that information. For example, a medicalprofessional that is assisting the patient with a medical issue may beprovided with medical history information regarding the patient, whereasa technician troubleshooting an issue with the treatment apparatus 70may be provided with a much more limited set of information regardingthe patient. The technician, for example, may be given only thepatient's name. The patient profile display 130 may includepseudonymized data and/or anonymized data or use any privacy enhancingtechnology to prevent confidential patient data from being communicatedin a way that could violate patient confidentiality requirements. Suchprivacy enhancing technologies may enable compliance with laws,regulations, or other rules of governance such as, but not limited to,the Health Insurance Portability and Accountability Act (HIPAA), or theGeneral Data Protection Regulation (GDPR), wherein the patient may bedeemed a “data subject”.

In some embodiments, the patient profile display 130 may presentinformation regarding the treatment plan for the patient to follow inusing the treatment apparatus 70. Such treatment plan information may belimited to an assistant who is a medical professional, such as a doctoror physical therapist. For example, a medical professional assisting thepatient with an issue regarding the treatment regimen may be providedwith treatment plan information, whereas a technician troubleshooting anissue with the treatment apparatus 70 may not be provided with anyinformation regarding the patient's treatment plan.

In some embodiments, one or more recommended treatment plans and/orexcluded treatment plans may be presented in the patient profile display130 to the assistant. The one or more recommended treatment plans and/orexcluded treatment plans may be generated by the artificial intelligenceengine 11 of the server 30 and received from the server 30 in real-timeduring, inter alia, a telemedicine or telehealth session.

The example overview display 120 shown in FIG. 5 also includes a patientstatus display 134 presenting status information regarding a patientusing the treatment apparatus. The patient status display 134 may takethe form of a portion or region of the overview display 120, as shown inFIG. 5, although the patient status display 134 may take other forms,such as a separate screen or a popup window. The patient status display134 includes sensor data 136 from one or more of the external sensors82, 84, 86, and/or from one or more internal sensors 76 of the treatmentapparatus 70. In some embodiments, the patient status display 134 maypresent other data 138 regarding the patient, such as last reported painlevel, or progress within a treatment plan.

User access controls may be used to limit access, including what data isavailable to be viewed and/or modified, on any or all of the userinterfaces 20, 50, 90, 92, 94 of the system 10. In some embodiments,user access controls may be employed to control what information isavailable to any given person using the system 10. For example, datapresented on the assistant interface 94 may be controlled by user accesscontrols, with permissions set depending on the assistant/user's needfor and/or qualifications to view that information.

The example overview display 120 shown in FIG. 5 also includes a helpdata display 140 presenting information for the assistant to use inassisting the patient. The help data display 140 may take the form of aportion or region of the overview display 120, as shown in FIG. 5. Thehelp data display 140 may take other forms, such as a separate screen ora popup window. The help data display 140 may include, for example,presenting answers to frequently asked questions regarding use of thepatient interface 50 and/or the treatment apparatus 70. The help datadisplay 140 may also include research data or best practices. In someembodiments, the help data display 140 may present scripts for answersor explanations in response to patient questions. In some embodiments,the help data display 140 may present flow charts or walk-throughs forthe assistant to use in determining a root cause and/or solution to apatient's problem. In some embodiments, the assistant interface 94 maypresent two or more help data displays 140, which may be the same ordifferent, for simultaneous presentation of help data for use by theassistant. for example, a first help data display may be used to presenta troubleshooting flowchart to determine the source of a patient'sproblem, and a second help data display may present script informationfor the assistant to read to the patient, such information to preferablyinclude directions for the patient to perform some action, which mayhelp to narrow down or solve the problem. In some embodiments, basedupon inputs to the troubleshooting flowchart in the first help datadisplay, the second help data display may automatically populate withscript information.

The example overview display 120 shown in FIG. 5 also includes a patientinterface control 150 presenting information regarding the patientinterface 50, and/or to modify one or more settings of the patientinterface 50. The patient interface control 150 may take the form of aportion or region of the overview display 120, as shown in FIG. 5. Thepatient interface control 150 may take other forms, such as a separatescreen or a popup window. The patient interface control 150 may presentinformation communicated to the assistant interface 94 via one or moreof the interface monitor signals 98 b. As shown in FIG. 5, the patientinterface control 150 includes a display feed 152 of the displaypresented by the patient interface 50. In some embodiments, the displayfeed 152 may include a live copy of the display screen currently beingpresented to the patient by the patient interface 50. In other words,the display feed 152 may present an image of what is presented on adisplay screen of the patient interface 50. In some embodiments, thedisplay feed 152 may include abbreviated information regarding thedisplay screen currently being presented by the patient interface 50,such as a screen name or a screen number. The patient interface control150 may include a patient interface setting control 154 for theassistant to adjust or to control one or more settings or aspects of thepatient interface 50. In some embodiments, the patient interface settingcontrol 154 may cause the assistant interface 94 to generate and/or totransmit an interface control signal 98 for controlling a function or asetting of the patient interface 50.

In some embodiments, the patient interface setting control 154 mayinclude collaborative browsing or co-browsing capability for theassistant to remotely view and/or control the patient interface 50. Forexample, the patient interface setting control 154 may enable theassistant to remotely enter text to one or more text entry fields on thepatient interface 50 and/or to remotely control a cursor on the patientinterface 50 using a mouse or touchscreen of the assistant interface 94.

In some embodiments, using the patient interface 50, the patientinterface setting control 154 may allow the assistant to change asetting that cannot be changed by the patient. For example, the patientinterface 50 may be precluded from accessing a language setting toprevent a patient from inadvertently switching, on the patient interface50, the language used for the displays, whereas the patient interfacesetting control 154 may enable the assistant to change the languagesetting of the patient interface 50. In another example, the patientinterface 50 may not be able to change a font size setting to a smallersize in order to prevent a patient from inadvertently switching the fontsize used for the displays on the patient interface 50 such that thedisplay would become illegible to the patient, whereas the patientinterface setting control 154 may provide for the assistant to changethe font size setting of the patient interface 50.

The example overview display 120 shown in FIG. 5 also includes aninterface communications display 156 showing the status ofcommunications between the patient interface 50 and one or more otherdevices 70, 82, 84, such as the treatment apparatus 70, the ambulationsensor 82, and/or the goniometer 84. The interface communicationsdisplay 156 may take the form of a portion or region of the overviewdisplay 120, as shown in FIG. 5. The interface communications display156 may take other forms, such as a separate screen or a popup window.The interface communications display 156 may include controls for theassistant to remotely modify communications with one or more of theother devices 70, 82, 84. For example, the assistant may remotelycommand the patient interface 50 to reset communications with one of theother devices 70, 82, 84, or to establish communications with a new oneof the other devices 70, 82, 84. This functionality may be used, forexample, where the patient has a problem with one of the other devices70, 82, 84, or where the patient receives a new or a replacement one ofthe other devices 70, 82, 84.

The example overview display 120 shown in FIG. 5 also includes anapparatus control 160 for the assistant to view and/or to controlinformation regarding the treatment apparatus 70. The apparatus control160 may take the form of a portion or region of the overview display120, as shown in FIG. 5. The apparatus control 160 may take other forms,such as a separate screen or a popup window. The apparatus control 160may include an apparatus status display 162 with information regardingthe current status of the apparatus. The apparatus status display 162may present information communicated to the assistant interface 94 viaone or more of the apparatus monitor signals 99 b. The apparatus statusdisplay 162 may indicate whether the treatment apparatus 70 is currentlycommunicating with the patient interface 50. The apparatus statusdisplay 162 may present other current and/or historical informationregarding the status of the treatment apparatus 70.

The apparatus control 160 may include an apparatus setting control 164for the assistant to adjust or control one or more aspects of thetreatment apparatus 70. The apparatus setting control 164 may cause theassistant interface 94 to generate and/or to transmit an apparatuscontrol signal 99 for changing an operating parameter of the treatmentapparatus 70, (e.g., a pedal radius setting, a resistance setting, atarget RPM, etc.). The apparatus setting control 164 may include a modebutton 166 and a position control 168, which may be used in conjunctionfor the assistant to place an actuator 78 of the treatment apparatus 70in a manual mode, after which a setting, such as a position or a speedof the actuator 78, can be changed using the position control 168. Themode button 166 may provide for a setting, such as a position, to betoggled between automatic and manual modes. In some embodiments, one ormore settings may be adjustable at any time, and without having anassociated auto/manual mode. In some embodiments, the assistant maychange an operating parameter of the treatment apparatus 70, such as apedal radius setting, while the patient is actively using the treatmentapparatus 70. Such “on the fly” adjustment may or may not be availableto the patient using the patient interface 50. In some embodiments, theapparatus setting control 164 may allow the assistant to change asetting that cannot be changed by the patient using the patientinterface 50. For example, the patient interface 50 may be precludedfrom changing a preconfigured setting, such as a height or a tiltsetting of the treatment apparatus 70, whereas the apparatus settingcontrol 164 may provide for the assistant to change the height or tiltsetting of the treatment apparatus 70.

The example overview display 120 shown in FIG. 5 also includes a patientcommunications control 170 for controlling an audio or an audiovisualcommunications session with the patient interface 50. The communicationssession with the patient interface 50 may comprise a live feed from theassistant interface 94 for presentation by the output device of thepatient interface 50. The live feed may take the form of an audio feedand/or a video feed. In some embodiments, the patient interface 50 maybe configured to provide two-way audio or audiovisual communicationswith a person using the assistant interface 94. Specifically, thecommunications session with the patient interface 50 may includebidirectional (two-way) video or audiovisual feeds, with each of thepatient interface 50 and the assistant interface 94 presenting video ofthe other one. In some embodiments, the patient interface 50 may presentvideo from the assistant interface 94, while the assistant interface 94presents only audio or the assistant interface 94 presents no live audioor visual signal from the patient interface 50. In some embodiments, theassistant interface 94 may present video from the patient interface 50,while the patient interface 50 presents only audio or the patientinterface 50 presents no live audio or visual signal from the assistantinterface 94.

In some embodiments, the audio or an audiovisual communications sessionwith the patient interface 50 may take place, at least in part, whilethe patient is performing the rehabilitation regimen upon the body part.The patient communications control 170 may take the form of a portion orregion of the overview display 120, as shown in FIG. 5. The patientcommunications control 170 may take other forms, such as a separatescreen or a popup window. The audio and/or audiovisual communicationsmay be processed and/or directed by the assistant interface 94 and/or byanother device or devices, such as a telephone system, or avideoconferencing system used by the assistant while the assistant usesthe assistant interface 94. Alternatively, or additionally, the audioand/or audiovisual communications may include communications with athird party. For example, the system 10 may enable the assistant toinitiate a 3-way conversation regarding use of a particular piece ofhardware or software, with the patient and a subject matter expert, suchas a medical professional or a specialist. The example patientcommunications control 170 shown in FIG. 5 includes call controls 172for the assistant to use in managing various aspects of the audio oraudiovisual communications with the patient. The call controls 172include a disconnect button 174 for the assistant to end the audio oraudiovisual communications session. The call controls 172 also include amute button 176 to temporarily silence an audio or audiovisual signalfrom the assistant interface 94. In some embodiments, the call controls172 may include other features, such as a hold button (not shown). Thecall controls 172 also include one or more record/playback controls 178,such as record, play, and pause buttons to control, with the patientinterface 50, recording and/or playback of audio and/or video from theteleconference session. The call controls 172 also include a video feeddisplay 180 for presenting still and/or video images from the patientinterface 50, and a self-video display 182 showing the current image ofthe assistant using the assistant interface. The self-video display 182may be presented as a picture-in-picture format, within a section of thevideo feed display 180, as shown in FIG. 5. Alternatively, oradditionally, the self-video display 182 may be presented separatelyand/or independently from the video feed display 180.

The example overview display 120 shown in FIG. 5 also includes athird-party communications control 190 for use in conducting audioand/or audiovisual communications with a third party. The third-partycommunications control 190 may take the form of a portion or region ofthe overview display 120, as shown in FIG. 5. The third-partycommunications control 190 may take other forms, such as a display on aseparate screen or a popup window. The third-party communicationscontrol 190 may include one or more controls, such as a contact listand/or buttons or controls to contact a third-party regarding use of aparticular piece of hardware or software, e.g., a subject matter expert,such as a medical professional or a specialist. The third-partycommunications control 190 may include conference calling capability forthe third party to simultaneously communicate with both the assistantvia the assistant interface 94, and with the patient via the patientinterface 50. For example, the system 10 may provide for the assistantto initiate a 3-way conversation with the patient and the third party.

FIG. 6 shows an example block diagram of training a machine learningmodel 13 to output, based on data 600 pertaining to the patient, atreatment plan 602 for the patient according to the present disclosure.Data pertaining to other patients may be received by the server 30. Theother patients may have used various treatment apparatuses to performtreatment plans. The data may include characteristics of the otherpatients, the details of the treatment plans performed by the otherpatients, and/or the results of performing the treatment plans (e.g., apercent of recovery of a portion of the patients' bodies, an amount ofrecovery of a portion of the patients' bodies, an amount of increase ordecrease in muscle strength of a portion of patients' bodies, an amountof increase or decrease in range of motion of a portion of patients'bodies, etc.).

As depicted, the data has been assigned to different cohorts. Cohort Aincludes data for patients having similar first characteristics, firsttreatment plans, and first results. Cohort B includes data for patientshaving similar second characteristics, second treatment plans, andsecond results. For example, cohort A may include first characteristicsof patients in their twenties without any medical conditions whounderwent surgery for a broken limb; their treatment plans may include acertain treatment protocol (e.g., use the treatment apparatus 70 for 30minutes 5 times a week for 3 weeks, wherein values for the properties,configurations, and/or settings of the treatment apparatus 70 are set toX (where X is a numerical value) for the first two weeks and to Y (whereY is a numerical value) for the last week).

Cohort A and cohort B may be included in a training dataset used totrain the machine learning model 13. The machine learning model 13 maybe trained to match a pattern between characteristics for each cohortand output the treatment plan that provides the result. Accordingly,when the data 600 for a new patient is input into the trained machinelearning model 13, the trained machine learning model 13 may match thecharacteristics included in the data 600 with characteristics in eithercohort A or cohort B and output the appropriate treatment plan 602. Insome embodiments, the machine learning model 13 may be trained to outputone or more excluded treatment plans that should not be performed by thenew patient.

FIG. 7 illustrates a block diagram of a system 700 for implementingdynamic treatment environments based on patient information, accordingto some embodiments. As shown in FIG. 7, the system 700 may include adata source 15, a server 30, a patient interface 50, a treatmentapparatus 70, and local devices 750, 760. Notwithstanding the specificillustrations in FIG. 7, the number and/or organization of the variouscomputing devices illustrated in FIG. 7 is not meant to be limiting. Tothe contrary, the system 700 may be adapted to omit and/or combine asubset of the devices illustrated in FIG. 7, or to include additionaldevices not illustrated in FIG. 7.

According to some embodiments, the data source 15 illustrated in FIG. 7may represent the data source 15 illustrated in FIG. 1 or may representany other data source(s) from which patient records may be obtained. Inany case, the data source 15 may be configured to store information forvarious patients—e.g., the patient data 44 illustrated in FIG. 1—whichis represented in FIG. 7 as patient records 702.

According to some embodiments, the patient records 702 may include, foreach patient, occupational characteristics of the patient,health-related characteristics of the patient, demographiccharacteristics of the patient, psychographic characteristics of thepatient, any other characteristics or attributes of the patient and thelike.

According to some embodiments, the occupational characteristics for agiven patient may include historical information about the patient'semployment experiences, travel experiences, social interactions, and thelike. For example, if a given patient is an active armed forces/militaryservice member, then the employment experience information may includethe patient's job roles, deployment history, rankings, and the like.

According to some embodiments, the health-related characteristics of thepatent may include historical information about the patient's health,including a history of the patient's interactions with medicalprofessionals, diagnoses received, prescriptions received, surgicalprocedures undertaken, past and/or ongoing medical conditions, dietaryneeds and/or habits, and the like. For example, the patient records 702for a given patient may indicate that the patient has, e.g., ongoingendocrinological issues, where such issues affect the patient's overallpsychological wellbeing.

According to some embodiments, the demographic characteristics for agiven patient may include information pertaining to the age, sex,ethnicity, weight, height, etc., of the patient. For example, thepatient records 702 for a given patient may indicate that the patient isa thirty-seven-year-old female of Asian descent.

Additionally, and according to some embodiments, the psychographiccharacteristics of the patient characteristics for a given patient mayinclude information relating to the attitudes, interests, opinions,beliefs, activities, overt behaviors, motivating behaviors, etc., of thepatient. For example, the patient records 702 for a given patient mayindicate that the patient has suffered from social anxiety disorder forthe past five years.

The foregoing types of patient records (occupational, health-related,demographic, psychographic, etc.) are merely exemplary and not meant tobe limiting; further, any type of patient record—such as thosepreviously herein—may be stored by the data source 15 consistent withthe scope of this disclosure.

According to some embodiments, the server 30 illustrated in FIG. 7 mayrepresent the server 30 illustrated in FIG. 1 or may represent anotherserver device configured to implement the different techniques set forthherein. According to some embodiments, the server 30 may generatemodified treatment plans 720 by using the various machine-learningfunctionalities described herein. For example, the server may utilizethe Al engine 11, the ML models 13, the training engine 9, etc.—whichare collectively represented in FIG. 7 as an assessment utility 712—togenerate the modified treatment plans 720.

According to some embodiments, the assessment utility 712 may beconfigured to receive data pertaining to patients who have performedmodified treatment plans 720 using different treatment apparatuses—e.g.,the patient interface 50, the treatment apparatus 70, the local devices750/760, and the like. In this regard, the data may includecharacteristics of the patients (e.g., patient records 702), the detailsof the modified treatment plans 720 performed by the patients, theresults of performing the modified treatment plans 720, and the like.The results may include, for example, the feedback 780/782 received fromthe patient interface 50 and the treatment apparatus 70, feedbackreceived from other devices (e.g., one or more of the clinicianinterface 20, the supervisory interface 90, the reporting interface 92,and the assistant interface 94), and the like. The foregoing feedbacksources are not meant to be limiting; further, the assessment utility712 may receive feedback from any conceivable source / individualconsistent with the scope of this disclosure.

According to some embodiments, the feedback may include changes to themodified treatment plans 720 requested by the patients (e.g., inrelation to performing the customized treatment plans 720), surveyanswers provided by the patients regarding their overall experiencerelated to the customized treatment plans 720, information related tothe patient's psychological and/or physical state during the treatmentsession (e.g., collected by sensors, by the patient, by a medicalprofessional, etc.), and the like. A more detailed description of thisfeedback is described below in relation to FIGS. 8A-8H.

Accordingly, the assessment utility 712 may utilize the machine-learningtechniques described herein to generate a modified treatment plan 720for a given patient. According to some embodiments, and as shown in FIG.7, a modified treatment plan 720 may include lighting parameters 722,sound parameters 724, notification parameters 726, augmented realityparameters 728, and other parameters 729. The foregoing parameters areexemplary and not meant to be limiting. The modified treatment plan 720may include any information necessary to facilitate a treatment sessionas described herein, e.g., connectivity information, pre-recordedcontent, interactive content, overarching treatment plan information(associated with the modified treatment plan 720), and so on.

Further, as shown in FIG. 7, according to the modified treatment plan720, the patient interface 50 and the treatment apparatus 70 may beconfigured to implement treatment utilities 730 and 740, respectively,to enable the patient interface 50 and the treatment apparatus 70 toself-configure. Although not illustrated in FIG. 7, one or more of thelocal devices 750/760 to which the patient interface 50 and thetreatment apparatus 70 are communicatively coupled may implementrespective treatment utilities that enable the local devices 750/760 toself-configure. This may not be required, however, in scenarios based onthe modified treatment plan 720 in which one or more of the patientinterface 50 and the treatment apparatus 70 possess the ability toadjust the configurations of one or more of the local devices 750/760.

According to some embodiments, the lighting parameters 722 may specifythe manner in which one or more light sources should be configured inorder to enhance the patient's overall experience. More specifically,the lighting parameters 722 may enable one or more devices on which themodified treatment plan 720 is being implemented—e.g., the patientinterface 50, the treatment apparatus 70, the local devices 750/760,etc. (hereinafter, “the recipient devices”)—to identify light sources,if any, that are relevant to (i.e., nearby) the user and are at leastpartially configurable according to the lighting parameters 722. Theconfigurational aspects may include, for example, the overall brightnessof a light source, the color tone of a light source, and the like. Inone example, a patient may have installed one or more smart lights forlight sources, e.g., Phillips Hue smart lights, Lutron Caséta smartlights, etc., in a room in which the patient typically conducts thetreatment sessions, where the brightness, the color tone, etc. of thesmart lights may be dynamically modified by commands. In anotherexample, a patient may have installed one or more traditional lights(e.g., incandescent, light emitting diode (LED), etc.) linked to acontroller that can affect the brightness, color tone, etc. output bythe one or more traditional lights. In any case, the recipient devicecan be configured to adjust identified light sources in accordance withthe lighting parameters 722.

According to some embodiments, the sound parameters 724 may specify themanner in which one or more sound sources may be configured to enhancethe patient's overall experience. More specifically, the soundparameters 724 may enable one or more of the recipient devices toidentify speakers (and/or amplifiers to which one or more speakers areconnected), if any, wherein both are nearby the user and at leastpartially configurable according to the sound parameters 724. Theconfigurational aspects may include, for example, an audio file and/orstream to play back, a volume at which to play back the audio fileand/or stream, sound settings (e.g., bass, treble, balance, etc.), andthe like. In one example, one of the recipient devices may be linked toone or more wired or wireless speakers, headphones, etc. located in aroom in which the patient typically conducts the treatment sessions.

According to some embodiments, the notification parameters 726 mayspecify the manner in which one or more nearby computing devices may beconfigured to enhance the patient's overall experience. Morespecifically, the notification parameters 726 may enable one or more ofthe recipient devices to adjust their own (or other devices')notification settings. In one example, this may include updatingconfigurations to suppress at least one of audible, visual, haptic, orphysical alerts, to minimize distractions to the patient during thetreatment session. This may also include updating a configuration tocause one or more of the recipient devices to transmit all electroniccommunications directly to an alternative target comprising one ofvoicemail, text, email, or other alternative electronic receiver.

According to some embodiments, the augmented reality parameters 728 mayspecify the manner in which one or more of the recipient devices areconfigured to provide an augmented reality experience to the patient.This may include, for example, updating a virtual background displayedon a display device communicatively coupled to one or more of therecipient devices. The techniques set forth herein are not limited toaugmented reality but may also apply to virtual (or other) realityimplementations. For example, the augmented reality parameters 728 mayinclude information enabling a patient to participate in a treatmentsession using a virtual reality headset configured in accordance withone or more of the lighting parameters 722, sound parameters 724,notification parameters 726, augmented reality parameters 728, or otherparameters 729. Further, any suitable immersive reality shall be deemedto be within the scope of the disclosure.

According to some embodiments, when a healthcare professional isconducting the treatment session, the other parameters 729 may representany other conceivable parameters that may be used to adjust thepatient's environment. The other parameters 729 may include, forexample, configuration parameters for exercise equipment, which aredescribed below in greater detail in relation to FIGS. 8G-8H.

Additionally, based on the parameters included in the modified treatmentplan 720, one or more of the recipient devices may take snapshots oftheir own (or other devices') existing configurations prior to adjustingsaid devices. In this manner, the one or more recipient devices mayrestore the configurations at the conclusion of the treatment session,thereby improving the patient's overall experience.

The foregoing types of parameters (lighting, sound, notification,augmented reality, other, etc.) are merely exemplary and not meant to belimiting; further, any type of parameter—such as those previouslyherein—may be adjusted consistent with the scope of this disclosure.

FIGS. 8A-8H illustrate conceptual diagrams for implementing a dynamictreatment environment based on a patient's information, according tosome embodiments. In particular, FIG. 8A illustrates an example scenarioin which the patient interface 50 receives a modified treatment plan720—which, as described above, may be provided by the server 30 usingthe manual and/or automated (e.g., machine-learning) techniquesdescribed herein. According to some embodiments, the patient interface50, in response to receiving the modified treatment plan 720, may outputa treatment utility interface 802 (e.g., on a display communicablycoupled to the patient interface 50). In the example illustrated in FIG.8A, the patient interface 50 may seek to discover nearby devices inresponse to identifying that the modified treatment plan 720 includesparameters (e.g., lighting, sound, notification, etc.) intended tomodify the configuration settings of nearby devices. As shown in FIG.8A, a patient operating the patient interface 50 may authorize thediscovery of nearby devices.

According to some embodiments, based on the parameters included in themodified treatment plan 720, the patient interface 50 may limit thediscovery process. For example, when only lighting parameters 722 (andnot the other parameters described herein) are included in the modifiedtreatment plan 720, the patient interface 50 may search for lightsources only. The patient interface 50 may also limit its discovery onlyto devices nearby the patient's known or likely location. For example,the patient interface 50 may reliably assume that devices coupled to thepatient interface 50 via low-energy communications (e.g., Bluetooth,Near Field Communication, etc.) are nearby. In another example, thepatient interface 50 may identify devices nearby based on names, tags,etc. assigned to the devices. For example, the patient interface 50 mayprompt the patient to indicate the name of the room in which the patientis currently sitting (e.g., “Home Office”), and, in turn, discovernearby devices based on the name of the room. In yet another example,machine-learning techniques may be implemented to reliably predict theroom in which the patient is located when the treatment session is aboutto begin. For example, the patient interface 50 may identify that,during virtually every prior treatment session, the patient was locatedin the “Home Office.” In this manner, the patient interface 50 mayautomatically limit its search for devices in that room prior tostarting each treatment session. Additionally, the patient interface 50may be configured to forego the discovery process after identifying thatthe same devices are consistently utilized over a threshold number oftreatment sessions.

FIG. 8B illustrates an example outcome of the patient interface 50presents nearby devices (as established in FIG. 8A) associated with thepatient interface 50. As shown in FIG. 8B, the patient interface 50indicates, by way of the treatment utility interface 802, that thepatient interface 50 has discovered office lights 830 (four differentlight sources under the name “Office Lights”), an office speaker 832(under the name “Office Speaker”), and a tablet 834 (under the name“Tablet”).

According to other embodiments, the treatment utility interface 802 mayenable the patient to add other devices not discovered by the patientinterface 50 when performing the search. For example, adding otherdevices may involve enabling the patient to select from a list ofdevices filtered out during discovery (e.g., per the techniquesdescribed in the foregoing paragraph). Adding other devices may alsoinvolve enabling the patient to enter information necessary to discoverand/or connect to other devices, such as device names, device addresses,device authentication information, and the like.

The foregoing discovery techniques are not meant to be limiting;further, any discovery technique, with any level of filtering, may beperformed consistent with the scope of this disclosure.

Additionally, and as shown in FIG. 8B, the treatment utility interface802 may enable the patient to modify the devices discovered by thepatient interface 50. For example, the patient may select the respective“Modify” button located next to a given group of discovered devices toadd, modify, or remove devices from the group. The treatment utilityinterface 802 may also enable the patient to instruct the patientinterface 50 to forget one or more groups of devices, both in atemporary capacity (e.g., for the current session only) or in a morepermanent capacity (e.g., until the patient removes the group from alist of forgotten devices). Such modifications may be communicated backto the server 30 in the form of feedback that may be used to improve theoverall accuracy of the machine-learning techniques described herein.

As shown in FIG. 8B, the patient may verify the accuracy of the list ofnearby devices presented in the treatment utility interface 802. Inturn, the treatment utility interface 802 may indicate to the patientthe recommended settings for the various devices when implementing themodified treatment plan 720, which is illustrated in FIG. 8C anddescribed below in greater detail.

As shown in FIG. 8C, the various parameters included in the modifiedtreatment plan 720 may be applied to the devices discovered (asestablished in FIGS. 8A-8B). For example, the lighting parameters 722 ofthe modified treatment plan 720 may involve setting the office lights830 to a 50% brightness level and a color tone of 2700K. The soundparameters 724 of the modified treatment plan 720 may involve settingthe office speaker 832 to play, e.g., a Mozart composition, at a volumelevel of 50 dB. Further, one or more audio files may be included in thesound parameters 724 to enable the office speaker 832 to play back audiodesigned to accompany the modified treatment plan 720. Alternatively, oradditionally, instructions for obtaining audio data may be included inthe sound parameters 724, e.g., a web address, credentials, etc. tostream audio designed to accompany the modified treatment plan 720.

In other embodiments, the notification parameters 726 of the modifiedtreatment plan 720 may involve suppressing all alerts on the patientinterface 50 and the tablet 834 such that, during the treatment session,the patient is not disturbed or distracted. Additionally, the augmentedreality parameters 728 of the modified treatment plan 720 may involveapplying a fixed/live ocean background to a video session that comprisesthe treatment session (e.g., wherein a clinician is superimposed overthe live ocean background). This background may be visible, for example,on a display device communicatively coupled to the patient interface 50(or other device with which the patient interface 50 is incommunication). Additionally, the other parameters 729 of the modifiedtreatment plan 720 may be used to apply any other additional settings toother recipient devices.

Additionally, as shown in FIG. 8C, the treatment utility interface 802may enable the patient to disable or modify the suggested settingslisted for the various devices. In the example illustrated in FIG. 8C,the patient opts to modify the suggested settings listed for the officespeaker 832, which is described below in greater detail in relation toFIG. 8D. Such modifications may be applied in a temporary capacity(e.g., for the current session only) or in a more permanent capacity(e.g., until the patient indicates it is acceptable to utilize therespective device as suggested by the modified treatment plan 720).Moreover, such modifications may be communicated back to the server 30in the form of feedback that may be used to improve the overall accuracyof the machine-learning techniques described herein.

As shown in FIG. 8D, the treatment utility interface 802 may enable thepatient to adjust the type and volume of the audio track that will beplayed back by the office speaker 832. For example, the patient mayselect alternative music (e.g., a Beethoven composition or,alternatively, e.g., a jazz, a pop, or a Reggae composition) if thepatient does not like Mozart's music. The patient may also select adifferent volume at which to output the music, e.g., a lower or highervolume than the volume recommended by the modified treatment plan 720.The patient is not limited, however, to modifying the parametersillustrated in FIG. 8D. To the contrary, the treatment utility interface802 may enable the patient to select other desired music from otherdesired sources (e.g., a local music library, streaming music services,etc.), to select from different playlists, and so on, consistent withthe scope of this disclosure.

In the example illustrated in FIG. 8D, the patient modifies the soundparameters 724 by selecting a soundtrack of Beethoven compositions(instead of Mozart compositions) and selecting a volume of 45 dB(instead of 50 dB). FIG. 8E illustrates the treatment utility interface802 after the patient has requested the changes (as established in FIG.8D). At this juncture, the patient confirms that the recommendedparameters are acceptable by selecting “YES”. In turn, and asillustrated in FIG. 8F, the treatment utility interface 802 causes thedifferent devices to reflect the settings illustrated in FIG. 8E.

As shown in FIG. 8F, the office lights 830 (illustrated as the officelights 830′ due to their adjusted settings) are configured to outputlight at a 50% brightness level and a 2700K color tone. The officespeaker 832 (illustrated as the office speaker 832′ due to its adjustedsettings) begins playing a Beethoven composition at 45 dB. Additionally,the tablet 834 (illustrated as the tablet 834′ due to its adjustedsettings) has entered into a silent mode. Finally, the patient interface50 (illustrated as the patient interface 50′ due to its adjustedsettings) has entered into a silent mode and is displaying a soothinglive ocean background as an augmented reality. At this juncture, thetraining session may begin.

Additionally, FIG. 8G illustrates an example scenario involving theincorporation of an exercise session into a treatment session (e.g., asa continuation of the treatment session established in FIGS. 8A-8F, as anew/different treatment session, etc.). As shown in FIG. 8G, theexercise session may involve the patient interface 50 discovering nearbyexercise devices. To identify the types of exercise devices compatiblewith the exercise session, this may involve, for example, referencingother parameters 729 included in the modified treatment plan 720. In theexample illustrated in FIG. 8G, the patient interface 50 discovers acycling trainer 840 named “Jim's Cycling Trainer” (based on, forexample, the other parameters 729 of the modified treatment plan 720indicating that cycling trainers are acceptable).

According to some embodiments, the cycling trainer 840 may represent thetreatment apparatus 70 described in FIGS. 1-4 or may represent adifferent cycling trainer. As shown in FIG. 8G, the cycling trainer 840may include one or more adjustable pedals 842 modifiable to establish arange of motion 844. The cycling trainer 840 may also include a resistor846 modifiable to establish a resistance 848 against the rotationalmotion of the one or more pedals 842.

As shown in FIG. 8G, the patient may confirm that the discovery of thecycling trainer 840 is accurate. Alternatively, the patient may attemptto add other exercise trainers by utilizing the same approachesdescribed in FIG. 8A for discovering other devices. In any case, asshown in FIG. 8H, the treatment utility interface 802 may displayrecommended settings (e.g., defined by the other parameters 729 of themodified treatment plan 720) for different components included on thecycling trainer 840. Again, the treatment utility interface 802 alsopermits the patient to modify/disable different settings (e.g., in amanner similar to that described in FIGS. 8C-8D).

When the patient approves the recommended settings, the patientinterface 50 may cause the recommended settings to be applied to thecycling trainer 840. This may include, for example, changing the rangeof motion of the pedals 842 to four inches to establish a range ofmotion 844′. This may also include changing the resistor 846 to 35% toestablish a resistance 848′ against the pedals 842. This may furtherinvolve setting the workout duration to 7.5 minutes (e.g., using aninternal clock on the cycling trainer 840 that causes the cyclingtrainer 840 to adjust its operation after 7.5 minutes have lapsed).

The components and configurable aspects of the cycling trainer 840 areexemplary; further, any cycling trainer may be utilized consistent withthe scope of this disclosure. It is also noted that the embodiments setforth herein are not limited to cycling trainers and that all forms ofexercise equipment, having varying adjustments and capabilities at anylevel of granularity, may be utilized consistent with the scope of thisdisclosure.

Additionally, it should be noted that the various settings describedthroughout FIGS. 8A-8H are not required to be static in naturethroughout the duration of the treatment session. To the contrary, themodified treatment plan 720 may include information that enables one ormore of the settings to change in response to conditions beingsatisfied. Such conditions may include, for example, an amount of timelapsing (e.g., five minutes after the treatment session starts), amilestone being hit (e.g., clinician/patient indicating a meditationperiod is been completed), an achievement being made (e.g., a lowresting heart rate being hit), and the like.

The foregoing examples of settings, conditions, etc., are not meant tobe limiting; further, any number and/or type of settings, conditions,etc., at any level of granularity, may be used to dynamically modify themodified treatment plan 720 consistent with the scope of thisdisclosure.

FIG. 9 shows an example embodiment of a method 900 for implementingdynamic treatment environments, according to some embodiments. Method900 includes operations performed by processors of a computing device(e.g., any component of FIG. 1, such as the server 30). In someembodiments, one or more operations of the method 900 are implemented incomputer instructions stored on a memory device and executed by aprocessing device. The operations of the method 900 may be performed insome combination with any of the operations of any of the methodsdescribed herein.

Regarding the method 900, at 902, the processing device—e.g., the server30—receives user data obtained from electronic or physical recordsassociated with a user. At 904, the server 30 generates a modifiedtreatment plan based on the user data obtained from electronic orphysical records associated with the user. At 910, the server 30provides the modified treatment plan to a treatment apparatus accessibleto the user. In turn, when the treatment apparatus implements themodified treatment plan, the modified treatment plan causes thetreatment apparatus to, based on the modified treatment plan: (1) updateat least one operational aspect of the treatment apparatus, and (2)update at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.

FIG. 10 shows an example embodiment of another method 1000 forimplementing dynamic treatment environments, according to someembodiments. Method 1000 includes operations performed by processors ofa computing device (e.g., any component of FIG. 1, such as the patientinterface 50, the treatment apparatus 70, and the like). In someembodiments, one or more operations of the method 1000 are implementedin computer instructions stored on a memory device and executed by aprocessing device. The operations of the method 1000 may be performed insome combination with any of the operations of any of the methodsdescribed herein.

Regarding the method 1000, at 1002, the processing device (e.g., atreatment apparatus) receives, from a server device (e.g., the server30), a treatment plan modified based on user data obtained fromelectronic or physical records associated with a user. At 1004, theprocessing device updates at least one operational aspect of thetreatment apparatus based on the modified treatment plan. At 1006, theprocessing device updates at least one operational aspect of at leastone other device communicably coupled to the treatment apparatus.

FIG. 11 shows an example computer system 1100 which can perform any oneor more of the methods described herein, in accordance with one or moreaspects of the present disclosure. In one example, computer system 1100may include a computing device and correspond to the assistanceinterface 94, reporting interface 92, supervisory interface 90,clinician interface 20, server 30 (including the Al engine 11), patientinterface 50, ambulatory sensor 82, goniometer 84, treatment apparatus70, pressure sensor 86, or any suitable component of FIG. 1. Thecomputer system 1100 may be capable of executing instructionsimplementing the one or more machine learning models 13 of theartificial intelligence engine 11 of FIG. 1. The computer system may beconnected (e.g., networked) to other computer systems in a LAN, anintranet, an extranet, or the Internet, including via the cloud or apeer-to-peer network. The computer system may operate in the capacity ofa server in a client-server network environment. The computer system maybe a personal computer (PC), a tablet computer, a wearable (e.g.,wristband), a set-top box (STB), a personal Digital Assistant (PDA), amobile phone, a camera, a video camera, an Internet of Things (IoT)device, or any device capable of executing a set of instructions(sequential or otherwise) that specify actions to be taken by thatdevice. Further, while only a single computer system is illustrated, theterm “computer” shall also be taken to include any collection ofcomputers that individually or jointly execute a set (or multiple sets)of instructions to perform any one or more of the methods discussedherein.

The computer system 1100 includes a processing device 1102, a mainmemory 1104 (e.g., read-only memory (ROM), flash memory, solid statedrives (SSDs), dynamic random-access memory (DRAM) such as synchronousDRAM (SDRAM)), a static memory 1106 (e.g., flash memory, solid statedrives (SSDs), static random-access memory (SRAM)), and a data storagedevice 1108, which communicate with each other via a bus 1110.

Processing device 1102 represents one or more general-purpose processingdevices such as a microprocessor, central processing unit, or the like.More particularly, the processing device 1102 may be a complexinstruction set computing (CISC) microprocessor, reduced instruction setcomputing (RISC) microprocessor, very long instruction word (VLIW)microprocessor, or a processor implementing other instruction sets orprocessors implementing a combination of instruction sets. Theprocessing device 1402 may also be one or more special-purposeprocessing devices such as an application specific integrated circuit(ASIC), a system on a chip, a field programmable gate array (FPGA), adigital signal processor (DSP), network processor, or the like. Theprocessing device 1402 is configured to execute instructions forperforming any of the operations and steps discussed herein.

The computer system 1100 may further include a network interface device1112. The computer system 1100 also may include a video display 1114(e.g., a liquid crystal display (LCD), a light-emitting diode (LED), anorganic light-emitting diode (OLED), a quantum LED, a cathode ray tube(CRT), a shadow mask CRT, an aperture grille CRT, a monochrome CRT), oneor more input devices 1116 (e.g., a keyboard and/or a mouse or agaming-like control), and one or more speakers 1118 (e.g., a speaker).In one illustrative example, the video display 1114 and the inputdevice(s) 1116 may be combined into a single component or device (e.g.,an LCD touch screen).

The data storage device 1116 may include a computer-readable medium 1120on which the instructions 1122 embodying any one or more of the methods,operations, or functions described herein is stored. The instructions1122 may also reside, completely or at least partially, within the mainmemory 1104 and/or within the processing device 1102 during executionthereof by the computer system 1100. As such, the main memory 1104 andthe processing device 1102 also constitute computer-readable media. Theinstructions 1122 may further be transmitted or received over a networkvia the network interface device 1112.

While the computer-readable storage medium 1120 is shown in theillustrative examples to be a single medium, the term “computer-readablestorage medium” should be taken to include a single medium or multiplemedia (e.g., a centralized or distributed database, and/or associatedcaches and servers) that store the one or more sets of instructions. Theterm “computer-readable storage medium” shall also be taken to includeany medium that is capable of storing, encoding, or carrying a set ofinstructions for execution by the machine and that cause the machine toperform any one or more of the methodologies of the present disclosure.The term “computer-readable storage medium” shall accordingly be takento include, but not be limited to, solid-state memories, optical media,and magnetic media.

Clause 1. A method for implementing dynamic treatment environments, themethod comprising, at a server device:

receiving user data obtained from records associated with a user;

generating, based on the user data, a modified treatment; and

sending, to a treatment apparatus accessible to the user, the modifiedtreatment plan, wherein the modified treatment plan causes the treatmentapparatus to:

-   -   update at least one operational aspect of the treatment        apparatus, and    -   update at least one operational aspect of at least one other        device communicatively coupled to the treatment apparatus.

Clause 2. The method of any clause herein, wherein the records containone or more of:

occupational characteristics of the user;

health-related characteristics of the user;

demographic characteristics of the user; or

psychographic characteristics of the user.

Clause 3. The method of any clause herein, wherein updating the at leastone operational aspect of the treatment apparatus comprises:

updating a virtual background displayed on a display devicecommunicatively coupled to the treatment apparatus, and

updating notification settings on the treatment apparatus.

Clause 4. The method of any clause herein, wherein updating thenotification settings comprises:

causing the treatment apparatus to suppress at least one of audible,visual, haptic, or physical alerts, and

causing the treatment apparatus to send all electronic communicationsdirectly to an alternative target comprising one of voicemail, text,email, or other alternative electronic receiver.

Clause 5. The method of any clause herein, wherein:

the at least one other device comprises at least one light source, and

updating the at least one operational aspect of the at least one lightsource comprises modifying one or more of a brightness or a color toneexhibited by at least one light source.

Clause 6. The method of any clause herein, wherein:

the at least one other device comprises at least one audio component,and

updating the at least one operational aspect of the at least one audiocomponent comprises modifying one or more of an output volume or anaudio stream played back by the at least one audio component.

Clause 7. The method of any clause herein, wherein the at least oneaudio component comprises at least one speaker or at least one amplifiercommunicably coupled to at least one speaker.

Clause 8. The method of any clause, wherein:

the at least one other device comprises at least one other computingdevice, and

updating the at least one operational aspect of the at least one othercomputing device comprises updating notification settings at the atleast one other computing device.

Clause 9. The method of any clause herein, wherein:

the at least one other device comprises a training device that includesat least one pedal or handle and at least one component that exertsresistance against a rotational motion of the at least one pedal orhandle; and

updating the at least one operational aspect of the training devicecomprises:

adjusting a range of motion of the at least one pedal, and

by way of the at least one component, adjusting an amount of resistanceagainst the rotational motion of the at least one pedal or handle.

Clause 10. The method of any clause herein, wherein, prior to updatingthe at least one operational aspect of the at least one other device,the treatment apparatus discovers the at least one other device on anauthorized network to which the treatment apparatus and the at least oneother device are communicably coupled.

Clause 11. A tangible, non-transitory computer-readable medium storinginstructions that, when executed, cause a processing device to:

receive user data obtained from records associated with a user;

generate a modified treatment plan based on the user data; and

sending, to a treatment apparatus accessible to the user, the modifiedtreatment plan, wherein the modified treatment plan causes the treatmentapparatus to:

update at least one operational aspect of the treatment apparatus, and

update at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.

Clause 12. The tangible, non-transitory computer-readable medium of anyclause herein, wherein the records contain one or more

occupational characteristics of the user;

health-related characteristics of the user;

demographic characteristics of the user; or

psychographic characteristics of the user.

Clause 13. The tangible, non-transitory computer-readable medium of anyclause herein, wherein updating the at least one operational aspect ofthe treatment apparatus comprises:

updating a virtual background displayed on a display devicecommunicatively coupled to the treatment apparatus, and

updating notification settings on the treatment apparatus.

Clause 14. The tangible, non-transitory computer-readable medium of anyclause herein, wherein updating the notification settings comprises:

causing the treatment apparatus to suppress at least one of audible,visual, haptic, or physical alerts, and

causing the treatment apparatus to send all electronic communicationsdirectly to an alternative target comprising one of voicemail, text,email, or other alternative electronic receiver.

Clause 15. The tangible, non-transitory computer-readable medium of anyclause herein, wherein:

the at least one other device comprises at least one light source, and

updating the at least one operational aspect of the at least one lightsource comprises modifying one or more of a brightness or a color toneexhibited by at least one light source.

Clause 16. The tangible, non-transitory computer-readable medium of anyclause herein, wherein:

the at least one other device comprises at least one audio component,and

updating the at least one operational aspect of the at least one audiocomponent comprises modifying one or more of an output volume or anaudio stream played back by the at least one audio component.

Clause 17. The tangible, non-transitory computer-readable medium of anyclause herein, wherein:

the at least one other device comprises a training device that includesat least one pedal or handle and at least one component that exertsresistance against a rotational motion of the at least one pedal orhandle; and

updating the at least one operational aspect of the training devicecomprises:

adjusting a range of motion of the at least one pedal, and

by way of the at least one component, adjusting an amount of resistanceagainst the rotational motion of the at least one pedal or handle.

Clause 18.A system comprising:

a memory device storing instructions; and

a processing device communicatively coupled to the memory device,wherein the processing device executes the instructions to:

receive user data obtained from records associated with a user;

generate a modified treatment plan based on the user data; and

sending, to a treatment apparatus accessible to the user, the modifiedtreatment plan, wherein the modified treatment plan causes the treatmentapparatus to:

update at least one operational aspect of the treatment apparatus, and

update at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.

Clause 19. The system of any clause herein, wherein the records containone or more of:

occupational characteristics of the user;

health-related characteristics of the user;

demographic characteristics of the user; or

psychographic characteristics of the user.

Clause 20. The system of any clause herein, wherein the records arefurther defined as one or more of electronic and physical records.

Clause 21. The system of any clause herein, wherein updating the atleast one operational aspect of the treatment apparatus comprises:

updating a virtual background displayed on a display devicecommunicatively coupled to the treatment apparatus, and

updating notification settings on the treatment apparatus.

Clause 22. The system of any clause herein, wherein the at least oneother device comprises at least one light source, and the at least onelight source having at least one operational aspect.

Clause 23. The system of any clause herein, further comprising updatingthe at least one operational aspect of the at least one light source.

Clause 24. The system of any clause herein, further comprising modifyingone or more of a brightness or a color tone exhibited by the at leastone light source.

Clause 25. The system of any clause herein, wherein the at least oneother device comprises at least one audio component having at least oneoperation aspect.

Clause 26. The system of any clause herein, further comprising updatingthe at least one operational aspect of the at least one audio component.

Clause 27. The system of any clause herein, further comprising modifyingone or more of an output volume or an audio stream played back by the atleast one audio component.

Clause 28. The system of any clause herein, wherein the at least oneother device comprises a training device that includes at least onerotatable pedal or handle and at least one component that exertsresistance against a rotational motion of the at least one pedal orhandle.

Clause 29. The system of any clause herein, wherein the training devicehas at least one operational aspect.

Clause 30. The system of any clause herein, wherein the at least oneoperational aspect of the training device comprises:

adjusting a range of motion of the at least one rotational pedal, and

adjusting an amount of the exerted resistance against the rotationalmotion of the at least one pedal or handle.

The above discussion is meant to be illustrative of the principles andvarious embodiments of the present disclosure. Numerous variations andmodifications will become apparent to those skilled in the art once theabove disclosure is fully appreciated. It is intended that the followingclaims be interpreted to embrace all such variations and modifications.

The various aspects, embodiments, implementations, or features of thedescribed embodiments can be used separately or in any combination. Theembodiments disclosed herein are modular in nature and can be used inconjunction with or coupled to other embodiments.

Consistent with the above disclosure, the examples of assembliesenumerated in the following clauses are specifically contemplated andare intended as a non-limiting set of examples.

What is claimed is:
 1. A system comprising: a memory device storinginstructions; and a processing device communicatively coupled to thememory device, wherein the processing device executes the instructionsto: receive user data obtained from records associated with a user;generate a modified treatment plan based on the user data; and sending,to a treatment apparatus accessible to the user, the modified treatmentplan, wherein the modified treatment plan causes the treatment apparatusto: update at least one operational aspect of the treatment apparatus,and update at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.
 2. The system ofclaim 1, wherein the records contain one or more of: occupationalcharacteristics of the user; health-related characteristics of the user;demographic characteristics of the user; or psychographiccharacteristics of the user.
 3. The system of claim 1, wherein therecords are further defined as one or more of electronic and physicalrecords.
 4. The system of claim 1, wherein updating the at least oneoperational aspect of the treatment apparatus comprises: updating avirtual background displayed on a display device communicatively coupledto the treatment apparatus, and updating notification settings on thetreatment apparatus.
 5. The system of claim 4, wherein the at least oneother device comprises at least one light source, and the at least onelight source having at least one operational aspect.
 6. The system ofclaim 5, further comprising updating the at least one operational aspectof the at least one light source.
 7. The system of claim 6, furthercomprising modifying one or more of a brightness or a color toneexhibited by the at least one light source.
 8. The system of claim 7,wherein the at least one other device comprises at least one audiocomponent having at least one operation aspect.
 9. The system of claim8, further comprising updating the at least one operational aspect ofthe at least one audio component.
 10. The system of claim 9, furthercomprising modifying one or more of an output volume or an audio streamplayed back by the at least one audio component.
 11. The system of claim10, wherein the at least one other device comprises a training devicethat includes at least one rotatable pedal or handle and at least onecomponent that exerts resistance against a rotational motion of the atleast one pedal or handle.
 12. The system of claim 11, wherein thetraining device has at least one operational aspect.
 13. The system ofclaim 12, wherein the at least one operational aspect of the trainingdevice comprises: adjusting a range of motion of the at least onerotatable pedal, and adjusting an amount of the exerted resistanceagainst the rotational motion of the at least one rotatable pedal orhandle.
 14. A method for implementing dynamic treatment environments,the method comprising, at a server device: receiving user data obtainedfrom records associated with a user; generating, based on the user data,a modified treatment; and sending, to a treatment apparatus accessibleto the user, the modified treatment plan, wherein the modified treatmentplan causes the treatment apparatus to: update at least one operationalaspect of the treatment apparatus, and update at least one operationalaspect of at least one other device communicatively coupled to thetreatment apparatus.
 15. The method of claim 14, wherein the recordscontain one or more of: occupational characteristics of the user;health-related characteristics of the user; demographic characteristicsof the user; or psychographic characteristics of the user.
 16. Themethod of claim 14, wherein updating the at least one operational aspectof the treatment apparatus comprises: updating a virtual backgrounddisplayed on a display device communicatively coupled to the treatmentapparatus, and updating notification settings on the treatmentapparatus.
 17. The method of claim 16, wherein updating the notificationsettings comprises: causing the treatment apparatus to suppress at leastone of audible, visual, haptic, or physical alerts, and causing thetreatment apparatus to send all electronic communications directly to analternative target comprising one of voicemail, text, email, or otheralternative electronic receiver.
 18. The method of claim 14, wherein:the at least one other device comprises at least one light source, andupdating the at least one operational aspect of the at least one lightsource comprises modifying one or more of a brightness or a color toneexhibited by the at least one light source.
 19. The method of claim 14,wherein: the at least one other device comprises at least one audiocomponent, and updating the at least one operational aspect of the atleast one audio component comprises modifying one or more of an outputvolume or an audio stream played back by the at least one audiocomponent.
 20. The method of claim 19, wherein the at least one audiocomponent comprises at least one speaker or at least one amplifiercommunicably coupled to the at least one speaker.
 21. The method ofclaim 14, wherein: the at least one other device comprises at least oneother computing device, and updating the at least one operational aspectof the at least one other computing device comprises updatingnotification settings at the at least one other computing device. 22.The method of claim 14, wherein: the at least one other device comprisesa training device that includes at least one pedal or handle and atleast one component that exerts resistance against a rotational motionof the at least one pedal or handle; and updating the at least oneoperational aspect of the training device comprises: adjusting a rangeof motion of the at least one pedal, and by way of the at least onecomponent, adjusting an amount of resistance against the rotationalmotion of the at least one pedal or handle.
 23. The method of claim 14,wherein, prior to updating the at least one operational aspect of the atleast one other device, the treatment apparatus discovers the at leastone other device on an authorized network to which the treatmentapparatus and the at least one other device are communicably coupled.24. A tangible, non-transitory computer-readable medium storinginstructions that, when executed, cause a processing device to: receiveuser data obtained from records associated with a user; generate amodified treatment plan based on the user data; and sending, to atreatment apparatus accessible to the user, the modified treatment plan,wherein the modified treatment plan causes the treatment apparatus to:update at least one operational aspect of the treatment apparatus, andupdate at least one operational aspect of at least one other devicecommunicatively coupled to the treatment apparatus.
 25. The tangible,non-transitory computer-readable medium of claim 24, wherein the recordscontain one or more occupational characteristics of the user;health-related characteristics of the user; demographic characteristicsof the user; or psychographic characteristics of the user.
 26. Thetangible, non-transitory computer-readable medium of claim 24, whereinupdating the at least one operational aspect of the treatment apparatuscomprises: updating a virtual background displayed on a display devicecommunicatively coupled to the treatment apparatus, and updatingnotification settings on the treatment apparatus.
 27. The tangible,non-transitory computer-readable medium of claim 26, wherein updatingthe notification settings comprises: causing the treatment apparatus tosuppress at least one of audible, visual, haptic, or physical alerts,and causing the treatment apparatus to send all electroniccommunications directly to an alternative target comprising one ofvoicemail, text, email, or other alternative electronic receiver. 28.The tangible, non-transitory computer-readable medium of claim 24,wherein: the at least one other device comprises at least one lightsource, and updating the at least one operational aspect of the at leastone light source comprises modifying one or more of a brightness or acolor tone exhibited by at least one light source.
 29. The tangible,non-transitory computer-readable medium of claim 24, wherein: the atleast one other device comprises at least one audio component, andupdating the at least one operational aspect of the at least one audiocomponent comprises modifying one or more of an output volume or anaudio stream played back by the at least one audio component.
 30. Thetangible, non-transitory computer-readable medium of claim 24, wherein:the at least one other device comprises a training device that includesat least one pedal or handle and at least one component that exertsresistance against a rotational motion of the at least one pedal orhandle; and updating the at least one operational aspect of the trainingdevice comprises: adjusting a range of motion of the at least one pedal,and by way of the at least one component, adjusting an amount ofresistance against the rotational motion of the at least one pedal orhandle.